made recomended changes, removed old logos and placed hexsticker in c…

…orrect location

DESCRIPTION

@@ -68,8 +68,8 @@ Description: An interface to subnational and national level COVID-19 data
     the UK, and from other Covid-19 data collections, including the World
     Health Organisation (WHO), European Centre for Disease Prevention and
     Control (ECDC), John Hopkins University (JHU), Google Open Data and
-    others. Designed to streamline Covid-19 data extraction, cleaning,
-    and processing from a range of data sources in an open and transparent
+    others. Designed to streamline Covid-19 data extraction, cleaning, and
+    processing from a range of data sources in an open and transparent
     way. This allows users to inspect and scrutinise the data, and tools
     used to process it, at every step. For all countries supported, data
     includes a daily time-series of cases. Wherever available data is also
@@ -103,6 +103,7 @@ Imports:
     xml2
 Suggests:
     ggplot2,
+    ggspatial,
     knitr,
     mockery,
     pkgdown,

README.Rmd

@@ -11,22 +11,7 @@ knitr::opts_chunk$set(
 )
 ```
 
-
-# Hexsticker designs
-
-### Design 1
-![Design 1](man/figures/logo1.png)
-
-### Design 2
-![design 2](man/figures/logo2.png)
-
-### Design 3
-![design 3](man/figures/logo3.png)
-
-### Design 5
-![design 5](man/figures/logo5.png)
-
-# Subnational data for the COVID-19 outbreak
+# Subnational data for the COVID-19 outbreak <img src="man/figures/logo.png" align="right" alt="" height="150" />
 
 [![Lifecycle: maturing](https://img.shields.io/badge/lifecycle-maturing-blue.svg)](https://lifecycle.r-lib.org/articles/stages.html) [![R-CMD-check](https://github.com/epiforecasts/covidregionaldata/workflows/R-CMD-check/badge.svg)](https://github.com/epiforecasts/covidregionaldata/actions) [![Codecov test coverage](https://codecov.io/gh/epiforecasts/covidregionaldata/branch/master/graph/badge.svg)](https://codecov.io/gh/epiforecasts/covidregionaldata?branch=master) [![Data status](https://img.shields.io/badge/Data-status-lightblue.svg?style=flat)](https://epiforecasts.io/covidregionaldata/articles/supported-countries.html) [![metacran downloads](http://cranlogs.r-pkg.org/badges/grand-total/covidregionaldata?color=ff69b4)](https://cran.r-project.org/package=covidregionaldata)
 

README.md

@@ -1,23 +1,5 @@
 
-# Hexsticker designs
-
-### Design 1
-
-![Design 1](man/figures/logo1.png)
-
-### Design 2
-
-![design 2](man/figures/logo2.png)
-
-### Design 3
-
-![design 3](man/figures/logo3.png)
-
-### Design 5
-
-![design 5](man/figures/logo5.png)
-
-# Subnational data for the COVID-19 outbreak
+# Subnational data for the COVID-19 outbreak <img src="man/figures/logo.png" align="right" alt="" height="150" />
 
 [![Lifecycle:
 maturing](https://img.shields.io/badge/lifecycle-maturing-blue.svg)](https://lifecycle.r-lib.org/articles/stages.html)
@@ -96,7 +78,7 @@ the temporary directory by default),
 
 ``` r
 start_using_memoise()
-#> Using a cache at: /tmp/Rtmp22YZr9
+#> Using a cache at: /tmp/RtmpXdh1Cd
 ```
 
 To stop using `memoise` use,
@@ -121,7 +103,7 @@ the Google COVID-19 open data project), use:
 ``` r
 nots <- get_national_data()
 #> Downloading data from https://covid19.who.int/WHO-COVID-19-global-data.csv
-#> Rows: 126,084
+#> Rows: 128,546
 #> Columns: 8
 #> Delimiter: ","
 #> chr  [3]: Country_code, Country, WHO_region
@@ -133,7 +115,7 @@ nots <- get_national_data()
 #> Cleaning data
 #> Processing data
 nots
-#> # A tibble: 126,084 x 15
+#> # A tibble: 128,690 x 15
 #>    date       un_region who_region country        iso_code cases_new cases_total
 #>    <date>     <chr>     <chr>      <chr>          <chr>        <dbl>       <dbl>
 #>  1 2020-01-03 Asia      EMRO       Afghanistan    AF               0           0
@@ -146,7 +128,7 @@ nots
 #>  8 2020-01-03 Americas  AMRO       Antigua & Bar… AG               0           0
 #>  9 2020-01-03 Americas  AMRO       Argentina      AR               0           0
 #> 10 2020-01-03 Asia      EURO       Armenia        AM               0           0
-#> # … with 126,074 more rows, and 8 more variables: deaths_new <dbl>,
+#> # … with 128,680 more rows, and 8 more variables: deaths_new <dbl>,
 #> #   deaths_total <dbl>, recovered_new <dbl>, recovered_total <dbl>,
 #> #   hosp_new <dbl>, hosp_total <dbl>, tested_new <dbl>, tested_total <dbl>
 ```
@@ -187,7 +169,7 @@ for example by level 1 region in the UK, use:
 ``` r
 uk_nots <- get_regional_data(country = "UK", verbose = FALSE)
 uk_nots
-#> # A tibble: 6,565 x 26
+#> # A tibble: 6,695 x 26
 #>    date       region   region_code cases_new cases_total deaths_new deaths_total
 #>    <date>     <chr>    <chr>           <dbl>       <dbl>      <dbl>        <dbl>
 #>  1 2020-01-30 East Mi… E12000004          NA          NA         NA           NA
@@ -200,7 +182,7 @@ uk_nots
 #>  8 2020-01-30 Scotland S92000003          NA          NA         NA           NA
 #>  9 2020-01-30 South E… E12000008          NA          NA         NA           NA
 #> 10 2020-01-30 South W… E12000009          NA          NA         NA           NA
-#> # … with 6,555 more rows, and 19 more variables: recovered_new <dbl>,
+#> # … with 6,685 more rows, and 19 more variables: recovered_new <dbl>,
 #> #   recovered_total <dbl>, hosp_new <dbl>, hosp_total <dbl>, tested_new <dbl>,
 #> #   tested_total <dbl>, areaType <chr>, cumCasesByPublishDate <dbl>,
 #> #   cumCasesBySpecimenDate <dbl>, newCasesByPublishDate <dbl>,

inst/WORDLIST

@@ -166,6 +166,7 @@ geocoding
 getRversion
 GFM
 ggplot
+ggspatial
 Gimma
 github
 Github

inst/make_hexsticker.R

@@ -22,78 +22,6 @@ regional_countries_l2 <- regional_countries %>%
 regional_countries_l1 <- regional_countries %>%
   filter(is.na(.data$level_2_region))
 
-# get world data
-world <- spData::world %>%
-  st_as_sf()
-
-
-# mark supported countries from the world data
-supported_countries <- world %>%
-  mutate(
-    fill = case_when(
-      name_long %in% countryname(regional_countries_l2[["origin"]], destination = "country.name.en") ~ "Level 2",
-      name_long %in% countryname(regional_countries[["origin"]], destination = "country.name.en") ~ "Level 1",
-      TRUE ~ "Unsupported"
-    )
-  )
-
-# make covid map
-covid_map_1 <- ggplot() +
-  ggspatial::layer_spatial(data = supported_countries, aes(fill = fill, color = fill, size = fill)) +
-  coord_sf(crs = "ESRI:54010") +
-  scale_fill_manual(
-    name = "",
-    values = c("#0072b2", "#cc79a7", "grey80")
-  ) +
-  scale_color_manual(
-    name = "",
-    values = c("black", "black", "#666666")
-  ) +
-  scale_size_manual(
-    name = "",
-    values = c(0.1, 0.1, 0.018)
-  ) +
-  cowplot::theme_minimal_grid(color = "white", line_size = 0.05) +
-  theme(legend.position = "none", axis.text.x = element_blank())
-
-logo1 <- sticker(
-  covid_map_1,
-  package = "covidregionaldata",
-  p_size = 48, s_x = 1, s_y = 0.8, s_width = 1.98, s_height = 1.98,
-  p_y = 1.45,
-  p_color = "white",
-  p_family = "useme",
-  h_color = "#646770",
-  h_fill = "#24A7DF",
-  filename = "man/figures/logo1.png",
-  u_size = 3.5,
-  dpi = 1000
-)
-
-# make logo 2
-supported_countries <- supported_countries %>%
-  filter(name_long != "Antarctica")
-
-covid_map_2 <- ggplot() +
-  ggspatial::layer_spatial(data = supported_countries, aes(fill = fill, size = fill, color = fill)) +
-  coord_sf(crs = "ESRI:54016") +
-  scale_fill_manual(
-    name = "",
-    values = c("#0072b2", "#cc79a7", "grey80")
-  ) +
-  scale_color_manual(
-    name = "",
-    values = c("black", "black", "#666666")
-  ) +
-  scale_size_manual(
-    name = "",
-    values = c(0.1, 0.1, 0.018)
-  ) +
-  theme_void() +
-  theme(legend.position = "none", axis.text.x = element_blank())
-
-print(covid_map_2)
-
 # Approach using Natural Earth data
 
 world_without_regions <- ne_countries(returnclass = "sf") %>%
@@ -136,67 +64,39 @@ regional_outlines <- ms_lines(
       ),
       returnclass = "sf"
     ),
-    keep = 0.5
+    keep = 0.1,
+    scale = 50
   )
 )
 
-
-covid_map_3 <- ggplot() +
+covid_map <- ggplot() +
   ggspatial::layer_spatial(data = world_without_regions, size = 0.01) +
   ggspatial::layer_spatial(
     data = regional_maps,
     aes(fill = region_code), size = 0.02
   ) +
   ggspatial::layer_spatial(
     data = regional_outlines,
-    aes(colour = 1), size = 0.1
+    aes(colour = factor(RANK)), size = 0.1
   ) +
   coord_sf(crs = "ESRI:54016") +
   scale_fill_fermenter(palette = "RdBu") +
   theme_void() +
+  scale_colour_manual(name = "", values = c("black", "black", "black")) +
   theme(legend.position = "none", axis.text.x = element_blank())
 
-print(covid_map_3)
-
-logo2 <- sticker(
-  covid_map_2,
-  package = "covidregionaldata",
-  p_size = 48, s_x = 0.96, s_y = 0.8, s_width = 1.7, s_height = 1.7,
-  p_y = 1.45,
-  p_color = "white",
-  p_family = "useme",
-  h_color = "#646770",
-  h_fill = "#24A7DF",
-  filename = "man/figures/logo2.png",
-  u_size = 3.5,
-  dpi = 1000
-)
+print(covid_map)
 
-logo3 <- sticker(
-  covid_map_2,
+logo <- sticker(
+  covid_map,
   package = "covidregionaldata",
   p_size = 48, s_x = 1, s_y = 0.8, s_width = 1.7, s_height = 1.7,
   p_y = 1.45,
   p_color = "white",
   p_family = "useme",
   h_color = "#646770",
   h_fill = "#24A7DF",
-  filename = "man/figures/logo3.png",
+  filename = "man/figures/logo.png",
   u_size = 3.5,
   dpi = 1000
 )
-
-logo4 <- sticker(
-  covid_map_3,
-  package = "covidregionaldata",
-  p_size = 48, s_x = 1, s_y = 0.8, s_width = 1.7, s_height = 1.7,
-  p_y = 1.45,
-  p_color = "white",
-  p_family = "useme",
-  h_color = "#646770",
-  h_fill = "#24A7DF",
-  filename = "man/figures/logo5.png",
-  u_size = 3.5,
-  dpi = 1000
-)
-